import numpy as np  
import pandas as pd
import random  
import math  

# data = load_data_from_attachment1()  

num_samples = 10  
specifications = pd.read_csv('data.csv', usecols=[0, 1, 2, 3])   # 厚度、宽度、碳含量、硅含量  
# 初始工艺参数（这里随机生成，实际中可能需要根据经验设定）  
initial_process_parameters = pd.read_csv('data.csv', usecols=[4, 5, 6, 7 ,8 ,9 ,10,11]) # 带钢速度、加热炉温度等8个参数  
hardness =  pd.read_csv('data.csv', usecols=[12])# 硬度能指标（实际中需要通过计算得到）  

# 计算硬度的函数（实际中需要替换为真实的计算模型）  
def calculate_hardness(specifications, process_parameters):  
    # 这里用随机模拟代替真实计算  
    return low + (high - low) * np.random.rand(len(specifications))  
low = 500  
high = 650
# 初始化解（这里随机生成，实际中可能需要根据经验设定）  
def initialize_solution():  
    return low + (high - low) * np.random.rand(num_samples, 8)  # 为每个样本生成一套工艺参数  
  
# 模拟退火算法  
def simulated_annealing():  
    current_solution = initialize_solution()  
    current_hardness = calculate_hardness(specifications, current_solution)  
    best_solution = current_solution  
    best_hardness = np.mean(current_hardness)  # 使用平均硬度作为评估标准  
    T = 1.0  # 初始温度  
    T_min = 0.0001  # 最低温度  
    alpha = 0.95  # 温度下降率  
      
    while T > T_min:  
        for i in range(100):  # 每个温度下的迭代次数  
            new_solution = current_solution + np.random.randn(num_samples, 8) * 0.1  # 在当前解的邻域内产生新解  
            new_hardness = calculate_hardness(specifications, new_solution)  
            new_average_hardness = np.mean(new_hardness)  
              
            # 如果新解更好，或者在一定概率下接受较差的解  
            if new_average_hardness < best_hardness or random.random() < math.exp((best_hardness - new_average_hardness) / T):  
                current_solution = new_solution  
                current_hardness = new_hardness  
                  
                # 更新最优解  
                if new_average_hardness < best_hardness:  
                    best_solution = new_solution  
                    best_hardness = new_average_hardness  
          
        T *= alpha  # 降低温度  
      
    return best_solution, best_hardness  
  
# 运行模拟退火算法  
best_solution, best_hardness = simulated_annealing()  
print("最优工艺参数:\n", best_solution)  
print("对应的平均硬度:", best_hardness)